def validation(self,
layout_validation_result_file_path,
record_num,
start_pos=0):
res = self.generate()
final_error = []
for item in res:
row = []
selected_sensors, unselected_sensors = item[0], item[1]
ok3d_linear = OrdinaryKriging(self.filtered_file_path,
self.pos_file_path, selected_sensors,
unselected_sensors, record_num,
start_pos, 'linear')
ok3d_linear_res = ok3d_linear.run()
final_error.append(self.accuracy_calculate(ok3d_linear_res))
csvfile = file(layout_validation_result_file_path, 'wb')
writer = csv.writer(csvfile)
tmp_rows = [item[0] for item in res]
writer.writerows(tmp_rows)
writer.writerow(final_error)
csvfile.close()
def energy(self):
tac = PickTactics()
selected_sensors, unselected_sensors = tac.fixed_tactic(self.state)
ok3d = OrdinaryKriging(self.filtered_file_path, self.pos_file_path,
selected_sensors, unselected_sensors,
self.each_sensor_number, 0, 'linear')
rmse = RMSE(ok3d.run())
#print(self.state)
res = rmse.temperature_error() + rmse.humidity_error()
if res <= self.goal:
super(LayoutOptimization, self).set_user_exit(0, 0)
return res
def validation(self, validation_result_file_path, record_num):
res = self.generate()
final_error = []
for item in res:
selected_sensors,unselected_sensors = item[0],item[1]
#print selected_sensors
#print unselected_sensors
ok3d_linear = OrdinaryKriging(self.filtered_file_path,self.pos_file_path,selected_sensors,unselected_sensors, record_num, 0,'linear')
ok3d_linear_res = ok3d_linear.run()
#print ok3d_linear_res
cal_res = self.accuracy_calculate(ok3d_linear_res)
final_error.append(cal_res)
#print final_error
csvfile = file(validation_result_file_path, 'wb')
writer = csv.writer(csvfile)
writer.writerow(final_error)
csvfile.close()
average_prediction /= len(group)
sum1 = 0.0
sum2 = 0.0
for item in group:
sum1 += (float(item[6]) - average_real) * (float(item[7]) -
average_prediction)
sum2 += (float(item[6])-average_real)*(float(item[6])-average_real)*\
(float(item[7])-average_prediction)*(float(item[7])-average_prediction)
total += sum1 / math.sqrt(sum2)
return total / len(self.data)
if __name__ == '__main__':
tac = PickTactics()
selected_sensors, unselected_sensors = tac.fixed_tactic(
[1, 2, 3, 4, 5, 11])
ok3d = OrdinaryKriging("../data/filter_data", "../data/pos/pos.csv",
selected_sensors, unselected_sensors, 2)
pearson1 = Pearson(ok3d.run())
idw = InverseDistanceWeighted("../data/filter_data", "../data/pos/pos.csv",
"../data/pos/distance.csv", selected_sensors,
unselected_sensors, 2)
pearson2 = Pearson(idw.run())
print pearson1.temperature_error()
print pearson1.humidity_error()
print pearson2.temperature_error()
print pearson2.humidity_error()
def temperature_error(self):
total = 0.0
for group in self.data:
tmp = 0.0
for item in group:
tmp += (float(item[5])-float(item[4]))*(float(item[5])-float(item[4]))
total += math.sqrt(tmp/len(group))
return total/len(self.data)
def humidity_error(self):
total = 0.0
for group in self.data:
tmp = 0.0
for item in group:
tmp += (float(item[7])-float(item[6]))*(float(item[7])-float(item[6]))
total += math.sqrt(tmp/len(group))
return total/len(self.data)
if __name__ == '__main__':
tac = PickTactics()
selected_sensors,unselected_sensors = tac.fixed_tactic([0,1,2])
ok3d = OrdinaryKriging("../data/filter_data","../data/pos/pos.csv",selected_sensors,unselected_sensors, 2,0,'linear')
tmp = ok3d.run()
print tmp
rmse = RMSE(tmp)
print rmse.temperature_error()
print rmse.humidity_error()
def validation(self, validation_result_file_path, record_num):
res = self.generate()
final_error = []
average_error = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
for item in res:
row = []
selected_sensors, unselected_sensors = item[0], item[1]
idw = InverseDistanceWeighted(self.filtered_file_path,
self.pos_file_path,
self.dis_file_path, selected_sensors,
unselected_sensors, record_num)
idw_res = idw.run()
ok3d_spherical = OrdinaryKriging(self.filtered_file_path,
self.pos_file_path,
selected_sensors,
unselected_sensors, record_num,
'spherical')
ok3d_spherical_res = ok3d_spherical.run()
ok3d_linear = OrdinaryKriging(self.filtered_file_path,
self.pos_file_path, selected_sensors,
unselected_sensors, record_num,
'linear')
ok3d_linear_res = ok3d_linear.run()
ok3d_power = OrdinaryKriging(self.filtered_file_path,
self.pos_file_path, selected_sensors,
unselected_sensors, record_num,
'power')
ok3d_power_res = ok3d_power.run()
#ok3d_gaussian = OrdinaryKriging(self.filtered_file_path,self.pos_file_path,selected_sensors,unselected_sensors, record_num, 'gaussian')
#ok3d_gaussian_res = ok3d_gaussian.run()
ok3d_exponential = OrdinaryKriging(self.filtered_file_path,
self.pos_file_path,
selected_sensors,
unselected_sensors, record_num,
'exponential')
ok3d_exponential_res = ok3d_exponential.run()
for i in range(3):
cal_res = self.accuracy_calculate(i, idw_res,
ok3d_spherical_res,
ok3d_linear_res,
ok3d_power_res,
ok3d_exponential_res)
row.append(cal_res)
for j in range(len(average_error)):
for k in range(len(average_error[0])):
average_error[j][k] += row[j][k]
final_error.append(row)
#print average_error
average_error = [[j / len(res) for j in i] for i in average_error]
#print average_error
for i in range(3):
csvfile = file(validation_result_file_path[i], 'wb')
writer = csv.writer(csvfile)
writer.writerow([
'idw温度',
'idw湿度',
'kriging_spherical温度',
'kriging_spherical湿度',
'kriging_linear温度',
'kriging_linear湿度',
'kriging_power温度',
'kriging_power湿度',
#'kriging_gaussian温度','kriging_gaussian湿度',
'kriging_exponential温度',
'kriging_exponential湿度'
])
tmp_rows = [item[i] for item in final_error]
writer.writerows(tmp_rows)
writer.writerow([
'平均值', '平均值', '平均值', '平均值', '平均值', '平均值', '平均值', '平均值', '平均值',
'平均值'
])
writer.writerow(average_error[i])
csvfile.close()
total = 0.0
for group in self.data:
tmp = 0.0
for item in group:
tmp += (float(item[5]) - float(item[4]))
total += tmp / len(group)
return total / len(self.data)
def humidity_error(self):
total = 0.0
for group in self.data:
tmp = 0.0
for item in group:
tmp += (float(item[7]) - float(item[6]))
total += tmp / len(group)
return total / len(self.data)
if __name__ == '__main__':
tac = PickTactics()
selected_sensors, unselected_sensors = tac.fixed_tactic(
[31, 32, 12, 7, 3, 11])
ok3d = OrdinaryKriging("../data/filter_data", "../data/pos/pos.csv",
selected_sensors, unselected_sensors, 2)
me = MeanError(ok3d.run())
print me.temperature_error()
print me.humidity_error()